Assessment of Flood Hazard Mapping Using a DEM-Based Approach and 2D Hydrodynamic Modeling

被引:2
作者
Amellah, Omayma [1 ]
Mignosa, Paolo [1 ]
Prost, Federico [1 ]
Aureli, Francesca [1 ]
机构
[1] Univ Parma, Dept Engn & Architecture, Parco Area Sci 181-A, I-43124 Parma, Italy
关键词
geomorphological modeling; 2D hydrodynamic modeling; DEM-based approach; floods; scaling laws; DELINEATION; AREAS; CLASSIFIERS; EXTRACTION; SIMULATION; ALGORITHM; DRAINAGE;
D O I
10.3390/w16131844
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
DEM-based approaches for assessing flood-prone areas have recently gained extensive attention due to their parsimony and cost-effectiveness. This work aims to test the capability of the Geomorphic Flood Index (GFI) to delineate flood-prone areas and the results performances while downscaling the calibration map. The accuracy was tested by examining the sensitivity to the exponent of the power function linking the flow depth in the river network and the upslope contributing area. Two approaches were selected: the first consisted of calibrating the GFI using a flood map generated through a 2D-SWE hydrodynamic model. The second consisted of correlating water depths with their corresponding upslope areas. The geomorphological model is able to effectively delineate flood susceptibility areas which, although on average larger than that obtained using the hydrodynamic model, provide a good starting point for any subsequent in-depth analysis. After calibration, an Objective Function of 0.21 and an Area Under the ROC Curve AUC = 92%, which is among the highest if compared with other cases in the literature, were obtained. Positive feedback was also obtained using a calibration map that covers only a rather limited portion of the basin. However, the small values of the scaling exponent obtained after calibration with the first method indicate substantial independence of the river depths from the upslope contributing areas. This leads to the belief that a simple power function is not particularly suitable for describing the relationships between these two variables.
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页数:19
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